As enterprise teams increasingly use AI tools, data security becomes an important issue. Many external AI tools often lack security measures, putting sensitive company data at risk.
For CTOs and CIOs, the biggest challenge lies in empowering their teams to effectively use AI tools while ensuring adherence to data protection regulations such as GDPR and CCPA.
Research by MIT Sloan Management Review underscores this challenge, revealing that over 70% of organisations are struggling to manage the emerging risks of AI. These findings highlight the critical need for organisations to secure sensitive information when integrating AI tools, ensuring that data remains protected and compliant with regulatory standards.
In contrast, many CRM platforms, including HubSpot, offer built-in AI features that keep your data within a secure environment. By processing and storing data within HubSpot's encrypted environment, companies can better control data security and compliance, minimising the risks associated with third-party solutions.
In this article, we explore how HubSpot's AI tools improve security and compliance and share best practices for organisations to protect sensitive data while using the full potential of Hubspot AI.
Frequently asked questions: ensuring security and compliance with HubSpot AI
Where is customer data processed and stored in HubSpot AI features, and how is it protected?
One of the key benefits of using HubSpot is that all your customer data is stored in one centralised platform, allowing for better control and security. Customer data processed by HubSpot AI features is stored in enterprise-grade security architecture, utilising a network of secure, geographically distributed, user-restricted databases managed by HubSpot. The customer data resides in isolated environments with AES-256 encryption at rest and TLS 1.2+ encryption in transit.
While some AI features leverage strategic partnerships with providers like OpenAI, these interactions occur through secure APIs with zero-retention policies, ensuring also that data is temporarily processed by these systems but not retained for model training. HubSpot also ensures, and is Audited annually by Independent Third Parties, that data storage and security align with regional legal requirements such as (but not limited to) GDPR and CCPA, ensuring data sovereignty and compliance with regional requirements across different jurisdictions.
How does HubSpot protect sensitive customer information during AI processing?
The HubSpot platform employs a multi-layered approach to sensitive data protection:
- Automated PII detection and classification systems;
- Granular role-based access controls (RBAC);
- Real-time monitoring through a dedicated Security Operations Center (SOC);
- Strict data processing agreements with AI partners prohibiting model training on customer data; and
- Comprehensive audit trails for all AI-driven processing activities.
During AI processing the sensitive data, including personal and business-related information, is protected through encryption in transit and at rest. Third-party providers (like OpenAI) access data only as needed for specific AI features and are prohibited from using it to train their models.
HubSpot utilises the mentioned enterprise controls to ensure additional safeguards, such as anonymising or deleting data as per customer agreements, are also maintained throughout the entire AI processing lifecycle.
What are the key security risks with HubSpot AI, and how are they mitigated?
Potential risks include unauthorised access or misuse of data processed by AI. HubSpot mitigates these risks by:
- Restricting third-party providers from retaining data for training;
- Enforcing encryption and robust access controls; and
- Ensuring users have visibility into and control over their data, including the ability to opt out of certain features.
Additionally, HubSpot strengthens security with Single Sign-On (SSO) and OTP/Authenticator options to further protect access to sensitive data. It is also crucial to work with trusted partners, such as Huble, who are ISO 27001 accredited. This certification ensures that your partners prioritise security, as you are only as strong as your weakest link, which is often third-party providers.
HubSpot addresses enterprise AI security risks through a sophisticated risk management framework:
- Data exposure: Mitigated through end-to-end encryption and isolated processing environments;
- Unauthorised access: Controlled via granular RBAC and continuous access monitoring, with mandatory Single Sign-On (SSO) implementation and Multi-Factor Authentication (MFA) through OTP/Authenticator options. This creates multiple layers of security verification beyond simple password protection;
- Third-party risk: Managed through strict contractual controls and zero-retention policies. This extends to partner selection - working with ISO 27001:2022 accredited partners like Huble demonstrates a commitment to security best practices, as organizations are only as secure as their weakest link. Third-party vendors without proper security accreditation will be your biggest vulnerable entry points into your ecosystem; and
- AI output validation: Implemented through automated verification protocols
Each risk vector is continuously monitored and assessed through regular penetration testing and third-party security audits. The platform employs a defense-in-depth strategy where multiple security controls work together:
- Mandatory SSO implementation reduces the risk of credential compromise
- MFA requirements ensure that even if credentials are exposed, additional verification is required
- ISO27001 accredited partners maintain security standards throughout the service delivery chain
- Regular security assessments verify the effectiveness of implemented controls
This comprehensive approach ensures that security is maintained not just within HubSpot's systems, but across the entire operational ecosystem, including third-party integrations and partner relationships.
Does data stay within HubSpot systems or get shared with providers like OpenAI?
When using AI features, some data (like call transcripts or CRM records) may be processed by third-party providers like OpenAI for generating outputs. However, HubSpot ensures that these providers do not store or use the data for model training.
HubSpot maintains a transparent data processing architecture where:
- Core data remains within HubSpot's secure infrastructure
- Limited data is processed through vetted AI partners for specific features
- All external processing occurs via secure APIs with zero-retention policies
- Complete audit trails track data movement across the ecosystem
This hybrid approach optimises AI capability while maintaining enterprise-grade security controls.
How does HubSpot ensure compliance with privacy laws like GDPR and CCPA?
HubSpot follows strict compliance protocols for major privacy regulations, including GDPR and CCPA. The platform's compliance framework includes:
- Automated data rights management for GDPR/CCPA
- Geographic data residency controls
- Granular consent management for AI features
- Regular compliance audits and certifications (SOC 2 Type II, ISO 27001)
- Documented data processing impact assessments
These controls ensure continuous compliance across jurisdictions while maintaining operational efficiency.
What specific security measures address AI-related risks?
HubSpot employs enterprise-specific security measures for AI operations (including but not limited to):
- AI-specific access controls and authentication
- Real-time monitoring of AI processing activities
- Automated threat detection and response
- Regular security assessments of AI features
- Comprehensive audit capabilities for AI interactions
- Encryption for data in transit and at rest.
- Transparency about data usage, including user input visibility.
- Restrictions on third-party data retention and use for training. Additionally, user permissions and controls are integral to its security framework.
What is HubSpot's plan if AI-related data issues arise?
The platform maintains an enterprise-grade incident response protocol:
- 24/7 SOC monitoring with automated detection
- Documented response procedures with designated response teams
- Immediate containment and investigation protocols
- Client notification within contractual SLAs
- Post-incident analysis and control enhancement
How does HubSpot’s AI security compare to other platforms?
HubSpot emphasises trust and transparency in its AI approach. Unlike some competitors, it prohibits third-party providers from using customer data for model training and provides detailed insights into how data moves through its systems. This proactive stance on transparency and user control distinguishes it in the enterprise market.
HubSpot distinguishes itself through:
- Industry-leading zero-retention policies for AI processing
- Complete transparency in AI operations and data flows
- Granular control over AI feature adoption
- Comprehensive audit capabilities
- Regular third-party security assessments
This enterprise-focused approach to AI security provides technical leaders with the controls and visibility needed for confident AI adoption.
Why AI security and compliance matter for enterprises using HubSpot
The risks of mishandling AI
AI tools rely on extensive customer data, much of which is sensitive or protected by privacy regulations such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA). Failure to protect this data can lead to compliance breaches that result in financial and legal consequences and undermine customer trust.
For healthcare and financial organisations operating in highly regulated environments, the stakes are even higher. A data breach involving medical records or financial transactions could cause catastrophic damage to an organisation's reputation and operations.
Key security and compliance challenges with AI in HubSpot
While organisations are using HubSpot's AI tools to increase efficiency and gain deeper insights, they also need to consider security and compliance challenges.
While these AI capabilities offer immense benefits, they also raise critical questions about data protection, privacy and ethical use. To ensure regulatory compliance and the protection of sensitive customer data, it is essential to carefully manage these risks.
Below we outline the key areas where security and compliance risks can arise and the steps organisations can take to manage them.
1. Data privacy and storage
AI tools in HubSpot analyze large volumes of customer data, including personally identifiable information (PII), behavioral patterns, and transactional history. Ensuring this data is securely stored and processed is non-negotiable. Enterprises must:
- Confirm that HubSpot’s data storage complies with regulations like GDPR or CCPA.
- Monitor where data is geographically stored, as cross-border data transfers may breach local privacy laws.
2. Algorithmic bias and ethical use
HubSpot’s AI-driven tools, such as lead scoring or email automation, depend on data-driven algorithms. If these algorithms are trained on biased or incomplete datasets, the results can perpetuate discrimination or unethical practices. Leaders must prioritize:
- Understanding how HubSpot’s AI makes decisions.
- Regularly auditing algorithms to detect and correct biases.
3. Cross-border data compliance
For global enterprises, navigating the patchwork of international data regulations is a significant challenge. AI-driven operations in HubSpot may involve transferring data across borders, which can lead to unintended compliance violations. Addressing this requires:
- Mapping data flows to ensure regulatory alignment.
- Implementing safeguards like data encryption and legal data transfer mechanisms (e.g., Standard Contractual Clauses).
4. Third-party integrations and API risks
HubSpot often integrates with a variety of third-party tools to expand functionality. However, these integrations increase the attack surface for cyber threats and compliance failures. Key considerations include:
- Vetting third-party vendors for their security practices.
- Ensuring that data shared via APIs complies with enterprise and regulatory standards.
5. Evolving regulatory landscape
AI regulations are still evolving, with increasing scrutiny from governments and industry bodies. Enterprises using HubSpot must stay ahead of these changes by:
- Regularly reviewing updates to privacy laws and AI-specific guidelines.
- Adapting internal policies to remain compliant with new standards.
To successfully overcome these challenges and ensure the safe, ethical use of AI, organisations need to take a proactive approach to compliance and data protection. Understanding the risks and implementing safeguards are critical to maintaining customer trust and avoiding regulatory penalties.
A HubSpot solutions provider like Huble helps businesses navigate these complexities, offering expertise and guidance on how to best secure AI features and stay compliant.
Take the next step toward secure AI adoption
To safely integrate AI, businesses must take action to secure data, ensure transparency in AI decisions, and manage third-party risks. Staying up to date with evolving privacy laws is also crucial to avoid penalties and protect customer trust.
HubSpot's AI tools are built with strong security and compliance features, making it easier to protect sensitive data. Working with a HubSpot solutions partner like Huble helps ensure your business successfully navigates these challenges.
If you’re ready to explore how to implement secure and compliant AI solutions tailored to your needs, reach out to our team today.
